Mr Xingjun Ma

  • Room: Level: 09 Room: 15
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • AI in Medical Training
  • Adversarial Deep Learning
  • Computer Vision
  • Weakly Supervised Machine Learning

Personal webpage

http://xingjunma.com/

Biography

Xingjun (Daniel) is a Postdoctoral Research Fellow in the School of Computing and Information Systems, The University of Melbourne. Daniel received his PhD degree from CIS, The University of Melbourne. He is a passionate researcher with particular interests in Deep Learning and Computer Vision topics: adversarial deep learning, noisy label learning and generative adversarial networks (GANs).

Recent publications

  1. Ma, X.; Li, B.; Wang, Y.; M. Erfani, S.; Wijewickrema, S.; Schoenebeck, G.; Song, D.; Houle, ME.; Bailey, J. Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. . ICLR. 2018.
  2. Wijewickrema, S.; Copson, B.; Ma, X.; Briggs, R.; Bailey, J.; Kennedy, G.; Oleary, S. Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear. Proceedings - IEEE Symposium on Computer-Based Medical Systems. IEEE. 2018, Vol. 2018-June, pp. 12-17. DOI: 10.1109/CBMS.2018.00010
  3. Ma, X.; Wang, Y.; Houle, ME.; Zhou, S.; Erfani, SM.; Xia, ST.; Wijewickrema, S.; Bailey, J. Dimensionality-Driven learning with noisy labels. 35th International Conference on Machine Learning, ICML 2018. JMLR. 2018, Vol. 8, pp. 5332-5341.
  4. Wang, Y.; Liu, W.; Ma, X.; Bailey, J.; Hongyuan, Z.; Song, L.; Xia, S-T. Iterative Learning with Open-set Noisy Labels. . The Computer Vision Foundation. 2018.
  5. Wijewickrema, S.; Ma, X.; Piromchai, P.; Briggs, R.; Bailey, J.; Kennedy, G.; O Leary, S. Providing automated real-time technical feedback for virtual reality based surgical training: Is the simpler the better?. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2018, Vol. 10947 LNAI, pp. 584-598. DOI: 10.1007/978-3-319-93843-1_43
  6. Ma, X.; Wijewickrema, S.; Zhou, S.; Zhou, Y.; Mhammedi, Z.; O'leary, S.; Bailey, J. Adversarial generation of real-time feedback with neural networks for Simulation-based training. IJCAI International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2017, pp. 3763-3769.
  7. Wijewickrema, S.; Copson, B.; Zhou, Y.; Ma, X.; Briggs, R.; Bailey, J.; Kennedy, G.; O'leary, S. Design and Evaluation of a Virtual Reality Simulation Module for Training Advanced Temporal Bone Surgery. Proceedings - IEEE Symposium on Computer-Based Medical Systems. IEEE. 2017, Vol. 2017-June, pp. 7-12. DOI: 10.1109/CBMS.2017.10
  8. Ma, X.; Wijewickrema, S.; Zhou, Y.; Zhou, S.; O Leary, S.; Bailey, J. Providing effective real-time feedback in simulation-based surgical training. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER. 2017, Vol. 10434 LNCS, pp. 566-574. DOI: 10.1007/978-3-319-66185-8_64
  9. Ma, X.; Wijewickrema, S.; Zhou, Y.; Copson, B.; Bailey, J.; Kennedy, G.; O'leary, S. Simulation for Training Cochlear Implant Electrode Insertion. Proceedings - IEEE Symposium on Computer-Based Medical Systems. IEEE. 2017, Vol. 2017-June, pp. 1-6. DOI: 10.1109/CBMS.2017.12
  10. Wang, Y.; Romano, S.; Nguyen, V.; Bailey, J.; Ma, X.; Xia, ST. Unbiased multivariate correlation analysis. 31st AAAI Conference on Artificial Intelligence, AAAI 2017. Unknown. 2017, pp. 2754-2760.